期刊
FRONTIERS IN PSYCHOLOGY
卷 14, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fpsyg.2023.1158172
关键词
automatic music generation system; algorithmic composition; music MedTech; emotion regulation; listener validation study; affective computing
This work introduces AffectMachine-Classical, a new music generation system capable of producing affective Classical music in real-time. It was designed to be used in biofeedback systems to help users become aware of and regulate their own dynamic affective states. The system has a rule-based, probabilistic architecture and has been validated through a listener study, showing its effectiveness in conveying target emotions to listeners. Future work aims to incorporate AffectMachine-Classical into biofeedback systems to enhance emotional well-being in listeners.
This work introduces a new music generation system, called AffectMachine-Classical, that is capable of generating affective Classic music in real-time. AffectMachine was designed to be incorporated into biofeedback systems (such as brain-computer-interfaces) to help users become aware of, and ultimately mediate, their own dynamic affective states. That is, this system was developed for music-based MedTech to support real-time emotion self-regulation in users. We provide an overview of the rule-based, probabilistic system architecture, describing the main aspects of the system and how they are novel. We then present the results of a listener study that was conducted to validate the ability of the system to reliably convey target emotions to listeners. The findings indicate that AffectMachine-Classical is very effective in communicating various levels of Arousal (R-2 = 0.96) to listeners, and is also quite convincing in terms of Valence (R-2 = 0.90). Future work will embed AffectMachine-Classical into biofeedback systems, to leverage the efficacy of the affective music for emotional wellbeing in listeners.
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